DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 6/27/23. Claims 1-20 are pending in this Office Action.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claims 6 is objected to because of the following informalities: Claim 6 recites the limitation of “generating workflow content based on the input intent by utilizing multiple computer applications to perform a sequence of successive processes that build on one another to generate the workflow content based on the knowledge graph”. It is not clear how the processes can be built “on one another” in the context of the sequence of successive processes. Appropriate correction is required.
Claims 1,8 and 15 recite the limitation of “..displaying content item together with selectable elements for interacting with the large language model”. There is insufficient antecedent basis for the recited “selectable elements” (plural form) because claims 1 , 8 and 15 only previously recite “a selectable element” (singular form ).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
2. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 8 and 15:
Step 1: Statutory Category ?: Yes. claim 1 recites a method (i.e., a “process”), claim 8 recites a system (i.e., a “machine”), claim 15 recites a non-transitory computer readable media (i.e., an article of manufacture) and which are statutory categories.
Claim 1:
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitation “ determining a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion . Except “by utilizing the large language model” language, nothing in the claim prevent the limitation from being performed in the human mind.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 1 recites additional elements:
“providing, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model ; receiving, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface;
based on determining the content item to provide to the client device, modifying the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model”
These additional elements are pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional element of “utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” amounts no more than using generic computer with generic model to apply the abstract idea.
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional elements of “utilizing the large language model” is at best the equivalent of merely adding the words “apply it” to the exception. The additional limitations of “providing…”;“receiving.. “ and “modifying…” do not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II. Even when considered in combination, the additional elements do not provide an inventive concept, claim 1 therefore is ineligible.
Claim 2 recites additional element of “wherein providing the intelligent assistant interface comprises providing a floating panel for display on the client device, wherein the floating panel includes a query panel for entering text queries and one or more action elements selectable for performing respective processes via computer applications” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 2 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 2 is not patent eligible.
Claim 3 recites additional element of “wherein receiving the indication of the user interaction with the selectable element comprises one or more of: receiving a selection of an action element for performing a predefined process utilizing an application installed on the client device or hosted on a server; receiving a text question for generating a response utilizing the large language model; or receiving a workflow prompt for generating workflow content by performing multiple processes utilizing multiple applications housed on different servers connected by a network” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 3 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 3 is not patent eligible.
. Claim 4 recites additional element of “identifying the content item corresponding to the input intent by analyzing the knowledge graph to perform a predefined process via an application installed on the client device or hosted on a server” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion . Except “by utilizing the large language model” language, nothing in the claim prevent the limitation from being performed in the human mind. The additional element of “utilizing the large language model to determine an input intent by processing the user interaction from the client device” amounts no more than using generic computer with generic model to apply the abstract idea and at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 4 therefore is ineligible.
Claim 5 recites additional element of “utilizing the large language model to determine an input intent by processing the user interaction from the client device; and utilizing the large language model to generate a response by analyzing the knowledge graph to determine graph information corresponding to the input intent for the response” . The utilizing large language model amounts no more than using generic computer with generic model to apply the abstract idea and is at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 5 therefore is ineligible.
Claim 6 recites additional element of “utilizing the large language model to determine an input intent by processing the user interaction from the client device” which amounts no more than using generic computer with generic model to apply the abstract idea and at best equivalent of merely adding the words “apply it” to the exception.
The additional element of “generating workflow content based on the input intent by utilizing multiple computer applications to perform a sequence of successive processes that build on one another to generate the workflow content based on the knowledge graph” amounts no more than mere instructions to apply the exception using generic computer and at best equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 6 therefore is ineligible.
Claim 7 recites additional element of “wherein modifying the intelligent assistant interface to present the embedded web browser comprises generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model” which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 7 therefore is ineligible.
Claim 8:
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitation “ determining a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion . Except “by utilizing the large language model” language, nothing in the claim prevent the limitation from being performed in the human mind.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 8 recites additional elements:
“providing, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model ; receiving, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface;
based on determining the content item to provide to the client device, modifying the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model”
These additional elements are pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional element of “ processor and non-transitory computer-readable medium ” which is recited at the very high level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components.
The additional element of “utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” amounts no more than using generic computer with generic model to apply the abstract idea.
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 8 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional elements of “processor and non-transitory computer-readable medium ” and “utilizing the large language model” is at best the equivalent of merely adding the words “apply it” to the exception. The additional limitations of “providing…”;“receiving.. “ and “modifying…” do not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II. Even when considered in combination, the additional elements do not provide an inventive concept, claim 8 therefore is ineligible.
Claim 9 recites additional element of “determining the relationships among the content items and the user accounts according to account behavior for a particular user account of the content management system; arranging nodes representing the user accounts and the content items within the content management system separated by distances reflecting the relationships defined by the account behavior of the particular user account; and connecting the nodes with edges defined by the distances between the nodes” which are mental processes that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of pen and paper. Claim 9 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 9 is not patent eligible.
Claim 10 recites additional element of “learn a repeated sequence of user interactions over time” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of pen and paper. The additional element of “automatically perform processes for the repeated sequence of user interactions without initiation by user input based on detecting a trigger event” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 10 therefore is ineligible.
Claim 11 recites additional element of “cause the system to generate a new action element to add to the intelligent assistant interface for the repeated sequence of user interactions” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 11 therefore is ineligible.
Claim 12 recites additional element of “cause the system to determine the content item to provide in response to the user interaction by: utilizing the large language model to determine an input intent by processing the user interaction from the client device; and utilizing the large language model to generate a response by analyzing the knowledge graph to determine graph information corresponding to the input intent for the response” . The utilizing large language model amounts no more than using generic computer with generic model to apply the abstract idea and is at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 12 therefore is ineligible.
Claim 13 recites additional element of “cause the system to modify the intelligent assistant interface to present the embedded web browser in response to determining that the content item from the knowledge graph is located at a server location displayable via a browser interface” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 13 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 13 is not patent eligible.
Claim 14 recites additional element of “cause the system to modify the intelligent assistant interface to present the embedded web browser by generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 14 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 14 is not patent eligible.
Claim 15:
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitation “ determining a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion . Except “by utilizing the large language model” language, nothing in the claim prevent the limitation from being performed in the human mind.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 15 recites additional elements:
“providing, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model ; receiving, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface;
based on determining the content item to provide to the client device, modifying the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model”
These additional elements are pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional element of “ processor and non-transitory computer-readable medium ” which is recited at the very high level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components.
The additional element of “utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system” amounts no more than using generic computer with generic model to apply the abstract idea.
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 15 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional elements of “processor and non-transitory computer-readable medium ” and “utilizing the large language model” is at best the equivalent of merely adding the words “apply it” to the exception. The additional limitations of “providing…”;“receiving.. “ and “modifying…” do not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II. Even when considered in combination, the additional elements do not provide an inventive concept, claim 15 therefore is ineligible.
Claim 16 recites additional element of “cause the at least one processor to provide the intelligent assistant interface by providing a floating panel for display on the client device, wherein the floating panel includes a query panel for entering text queries and one or more action elements selectable for performing respective processes via computer applications” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 16 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 16 is not patent eligible.
Claim 17 recites additional element of “learn a repeated sequence of user interactions over time; and automatically perform the repeated sequence of user interactions to generate the content item without initiation by user input based on detecting a trigger event” . The limitation of “learn a repeated sequence of user interactions over time” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of pen and paper. The additional element of “automatically perform processes for the repeated sequence of user interactions without initiation by user input based on detecting a trigger event” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 17 therefore is ineligible.
Claim 18 recites additional element of “based on automatically generating the content item, provide an edit option for editing the content item before providing to another client device” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 18 therefore is ineligible.
Claim 19 recites additional element of “modify the intelligent assistant interface to present the embedded web browser in response to determining that the content item from the knowledge graph is located at a server location displayable via a browser interface” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 19 therefore is ineligible.
Claim 20 recites additional element of “modify the intelligent assistant interface to present the embedded web browser by generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 20 therefore is ineligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-9, 11-16 and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kale et al.,(US Patent Application Publication 2018/0052884 A1, hereinafter “Kale”)
As to claim 1, Kale teaches a method comprising: providing, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model ; receiving, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface;(Kale par [0096] teaches user enters text input)
determining a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system (Kale par [0111] teaches during processing of a user query, the parsed input data elements from the user query may be matched against the dimensions in the knowledge graph to help match the user’s demands with the available supply of items. Kale par [0112] teaches the knowledge graph 808 may be based on the historical interaction of all users with an electronic marketplace over a period of time ) ; and
based on determining the content item to provide to the client device, modifying the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters)
As to claim 2, Kale teaches the method of claim 1, wherein providing the intelligent assistant interface comprises providing a floating panel for display on the client device, wherein the floating panel includes a query panel for entering text queries (Kale par [0096] teaches user enters text input)
and one or more action elements selectable for performing respective processes via computer applications. (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and show images of specific items or item groups available for purchase. The affirmation may be verbal reply or a selection of a particular displayed item)
As to claim 3, Kale teaches the method of claim 1, wherein receiving the indication of the user interaction with the selectable element comprises one or more of: receiving a selection of an action element for performing a predefined process utilizing an application installed on the client device or hosted on a server;
receiving a text question for generating a response utilizing the large language model; or receiving a workflow prompt for generating workflow content by performing multiple processes utilizing multiple applications housed on different servers connected by a network. (Kale par [0096] teaches user enters text input)
As to claim 4, Kale teaches the method of claim 1, wherein determining the content item to provide in response to the user interaction comprises:
utilizing the large language model to determine an input intent by processing the user interaction from the client device (Kale par [0038] teaches the artificial intelligence framework 128 further includes a natural language understanding component that operates to extract user intent and various intent parameters) ; and
identifying the content item corresponding to the input intent by analyzing the knowledge graph to perform a predefined process via an application installed on the client device or hosted on a server. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters)
As to claim 5, Kale teaches the method of claim 1, wherein determining the content item to provide in response to the user interaction comprises: utilizing the large language model to determine an input intent by processing the user interaction from the client device (Kale par [0038] teaches the artificial intelligence framework 128 further includes a natural language understanding component that operates to extract user intent and various intent parameters); and
utilizing the large language model to generate a response by analyzing the knowledge graph to determine graph information corresponding to the input intent for the response. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters)
As to claim 6, Kale teaches the method of claim 1, wherein determining the content item to provide in response to the user interaction comprises: utilizing the large language model to determine an input intent by processing the user interaction from the client device (Kale par [0038] teaches the artificial intelligence framework 128 further includes a natural language understanding component that operates to extract user intent and various intent parameters);
generating workflow content based on the input intent by utilizing multiple computer applications to perform a sequence of successive processes that build on one another to generate the workflow content based on the knowledge graph. (Kale par [0080] teaches extracting a user intent is performed by the NLE component 214 by breaking down into multiple parts. Each of the various parts of the overall problem of extracting user intent may be processed by a particular sub-component of the NLE sometimes separately and sometimes in combination. Kale par [0081] teaches sub-component includes a knowledge graph)
As to claim 7, Kale teaches the method of claim 1, wherein modifying the intelligent assistant interface to present the embedded web browser comprises generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model. (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and show images of specific items or item groups available for purchase. The affirmation may be verbal reply or a selection of a particular displayed item)
As to claim 8, Kale teaches a system comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor (Kale par [0024] teaches one or more processors) , cause the system to:
provide, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model, wherein the selectable element comprises one or more of a query panel for entering text queries or an action element selectable performing a process using a separate computer application (Kale par [0096] teaches user enters text input);
receive, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface (Kale par [0096] teaches user enters text input);
determine a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system (Kale par [0111] teaches during processing of a user query, the parsed input data elements from the user query may be matched against the dimensions in the knowledge graph to help match the user’s demands with the available supply of items. Kale par [0112] teaches the knowledge graph 808 may be based on the historical interaction of all users with an electronic marketplace over a period of time ); and
based on determining the content item to provide to the client device, modify the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters)
As to claim 9, Kale teaches the system of claim 8, further comprising instructions that, when executed by the at least one processor, cause the system to generate the knowledge graph by:
determining the relationships among the content items and the user accounts according to account behavior for a particular user account of the content management system (Kale par [0112] teaches the knowledge graph 808 may be based on the historical interaction of all users with an electronic marketplace over a period of time. Kale par [0114] teaches dimensions of the knowledge graph may now comprise the categories attributes and attribute values provided by previous user’s query inputs) ;
arranging nodes representing the user accounts and the content items within the content management system separated by distances reflecting the relationships defined by the account behavior of the particular user account; and connecting the nodes with edges defined by the distances between the nodes. (Kale par [0113] teaches regardless of the availability inventory, the knowledge graph 808 characterizes the search behavior of users, e.g. how users are attempting to find relevant items)
As to claim 11, Kale teaches the system of claim 10, further comprising instructions that, when executed by the at least one processor, cause the system to generate a new action element to add to the intelligent assistant interface for the repeated sequence of user interactions.(Kale par [0086] teaches the knowledge graph 808 may also use dominant (e.g., most frequently user -queried or most frequently occurring an item inventory) attributes pertaining to that item category , and dominant values for those attributes. Thus the NLE component 214 may provide as its output the dominant object, user intent , and knowledge graph 808 that is formulated along dimensions likely to be relevant to the user query)
As to claim 12, Kale teaches the system of claim 8, further comprising instructions that, when executed by the at least one processor, cause the system to determine the content item to provide in response to the user interaction by: utilizing the large language model to determine an input intent by processing the user interaction from the client device (Kale par [0038] teaches the artificial intelligence framework 128 further includes a natural language understanding component that operates to extract user intent and various intent parameters; and utilizing the large language model to generate a response by analyzing the knowledge graph to determine graph information corresponding to the input intent for the response. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters )
As to claim 13, Kale teaches the system of claim 8, further comprising instructions that, when executed by the at least one processor, cause the system to modify the intelligent assistant interface to present the embedded web browser in response to determining that the content item from the knowledge graph is located at a server location displayable via a browser interface. ( Kale par [0031] teaches web client 102 may access the intelligent personal assistance system 106 via web interface.. Kale Fig.12 and par [0121] teaches processing user input to generate suggestive prompts )
As to claim 14, Kale teaches the system of claim 8, further comprising instructions that, when executed by the at least one processor, cause the system to modify the intelligent assistant interface to present the embedded web browser (Kale par [0031] teaches web client 102 may access the intelligent personal assistance system 106 via web interface.) by generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” ) and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model. (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and show images of specific items or item groups available for purchase. The affirmation may be verbal reply or a selection of a particular displayed item)
As to claim 15, Kale teaches a non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause the at least one processor to: provide, for display on a client device, an intelligent assistant interface comprising a selectable element for interacting with a large language model; receive, from the client device, an indication of a user interaction with the selectable element of the intelligent assistant interface, wherein the user interaction comprises one or more of entering a text query or selecting an action element via the intelligent assistant interface; (Kale par [0096] teaches user enters text input);
determine a content item to provide to the client device in response to the user interaction by utilizing the large language model to analyze a knowledge graph defining relationships among content items and user accounts of a content management system (Kale par [0111] teaches during processing of a user query, the parsed input data elements from the user query may be matched against the dimensions in the knowledge graph to help match the user’s demands with the available supply of items. Kale par [0112] teaches the knowledge graph 808 may be based on the historical interaction of all users with an electronic marketplace over a period of time ); and
based on determining the content item to provide to the client device, modify the intelligent assistant interface to present an embedded web browser for displaying the content item together with selectable elements for interacting with the large language model. (Kale par [0115] teaches the NLU component 214 may deliver a concise knowledge graph 808, with dimensions having some relevance, to the dialog manager 216 along with the dominant object of user interest, user intent and related parameters)
As to claim 16, Kale teaches the non-transitory computer readable medium of claim 15, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to provide the intelligent assistant interface by providing a floating panel for display on the client device, wherein the floating panel includes a query panel for entering text queries (Kale par [0096] teaches user enters text input and one or more action elements selectable for performing respective processes via computer applications. (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and show images of specific items or item groups available for purchase. The affirmation may be verbal reply or a selection of a particular displayed item)
As to claim 19, Kale teaches the non-transitory computer readable medium of claim 15, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to modify the intelligent assistant interface to present the embedded web browser in response to determining that the content item from the knowledge graph is located at a server location displayable via a browser interface. ( Kale par [0031] teaches web client 102 may access the intelligent personal assistance system 106 via web interface.. Kale Fig.12 and par [0121] teaches processing user input to generate suggestive prompts )
As to claim 20, The non-transitory computer readable medium of claim 15, further comprising instructions that, when executed by the at least one processor, cause the at least one processor to modify the intelligent assistant interface to present the embedded web browser by generating a hybrid assistant-browser interface that includes a first area dedicated to the embedded web browser for displaying the content item (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” ) and a second area dedicated to the intelligent assistant interface that includes the selectable elements for interacting with the large language model. (Kale par [0127] teaches the prompt 1204 may thus announce “I round these sneakers:” and show images of specific items or item groups available for purchase. The affirmation may be verbal reply or a selection of a particular displayed item)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kale and further in view of Wang et al.(US Patent Application Publication 2013/0283283 A1, hereinafter “Wang”)
As to claim 10, Kale teaches the system of claim 8 but fails to expressly teach further comprising instructions that, when executed by the at least one processor, cause the system to: learn a repeated sequence of user interactions over time; and automatically perform processes for the repeated sequence of user interactions without initiation by user input based on detecting a trigger event.
However, Wang teaches learn a repeated sequence of user interactions over time; and automatically perform processes for the repeated sequence of user interactions without initiation by user input based on detecting a trigger event.(Wang par [0042] teaches suppose user often activated a browser application to read news at 9.00am. In this case, based on application usage history, the prediction subsystem may identify that the user is very likely to activate the browser at 0.00am and thus the device may even automatically connect to the news website which the user often visited without manual activation by the user)
Therefore , it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Kale and Wang to achieve the claimed invention. One would have been motivated to make such combination to increase the convenience for the user (Wang par [0008])
As to claim 17, see the above rejection of claim 10.
Claims 18 is rejected under 35 U.S.C. 103 as being unpatentable over Kale , Wang and further in view of Morales et al.(US Patent Application Publication 2024/0272920 A1, hereinafter “Morales”)
As to claim 18, Kale and Wang teach the non-transitory computer readable medium of claim 17 but fail teach further comprising instructions that, when executed by the at least one processor, cause the at least one processor to, based on automatically generating the content item, provide an edit option for editing the content item before providing to another client device.
However, Morales teaches cause the at least one processor to, based on automatically generating the content item, provide an edit option for editing the content item before providing to another client device.(Morales par [0092] teaches the instance of the individual content item may be editable via the automated communication)
Therefore , it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Kale, Wang and Morales to achieve the claimed invention. One would have been motivated to make such combination to increase work productivity amongst all users.(Morales par [0003])
Conclusion
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/HIEN L DUONG/Primary Examiner, Art Unit 2147